US 2010/0061596 A1 discloses a method of determining a similarity with a portion of a physiological motion, the method comprising the steps of:                obtaining a first image of an object;        obtaining a second image of the object;        determining a level of similarity between the first and the second image; and        correlating the determined level of similarity between the first and second images with a portion of the physiological motion.        
The document further discloses several refinements of the method. In particular, the document is directed to patient monitoring, such as monitoring breathing activity of a patient. Vital signal monitoring grows in significance in several fields of application, such as patient monitoring and monitoring sports and fitness activities, for example. Further beneficial applications can be envisaged. Although considerable progress in the field of monitoring performance has been achieved, it is still a challenge to provide for instant signal recognition and signal processing enabling immediate, so-to-say, on-line detection of desired vital signals. This applies in particular to hand-held mobile devices commonly lacking of sufficient computing power and typically exposed to challenging monitoring conditions and constraints.
A further challenge may arise from disturbances and restrictions which have to be taken into account for the detection of the desired signals. As known in the art, detection quality can be improved through applying obtrusive (or: tactile) measurement. For monitoring breathing activity or, in other words, respiration activity, obtrusive measurement devices may comprise belts or sensors which typically have to be attached to a subject's body. Furthermore, referring to remote detection approaches, prior art devices and methods may require markers or similar items which have to be applied to the subject to be observed. These markers can be remotely monitored since they provide sufficient “detectability” and may be considered prominent targets for a detecting device. Still, however, obtrusive measurement, either applied remotely or via tactile measurement devices, is considered unpleasant and uncomfortable by many observed subjects.
Remote unobtrusive measurement typically enables a recording or monitoring of the subject of interest without applying any components or “hardware” to the subject at all. Consequently, since no hardware markers are available, remote unobtrusive detection is widely subjected to disturbances. Recently, even mobile hand-held devices for remote monitoring of vital signals have been envisaged. Mobile hand-held devices are even more susceptible to disturbances since they are typically hand-operated without fixed support. Consequently, huge disturbances attributable to non-indicative device motion with respect to the subject to be monitored have to be expected.
Therefore, it has to be taken into account that the recorded data, such as captured reflective or emitted electromagnetic radiation (e.g., recorded image frames), typically comprises major signal components deriving from overall disturbances. Disturbance-related signal components overlay and affect the desired vital signals basically addressed when monitoring the subject. Overall disturbances may be attributed to changing luminance conditions and disturbing motion components, for example. Disturbing motion may arise from non-indicative motion of the subject itself, or from undesired motion of the detecting or sensing device. In particular with mobile hand-held monitoring devices, overall motion (or: global motion) is considered a huge challenge. Furthermore, particularly addressing respiration detection via remote unobtrusive measurement devices, subject motion-related signals are, so-to-say, attenuated in case the subject of interest is covered (at least partially), for instance, by clothes or even blankets. This applies in particular when sleeping or lying subjects are addressed. Under such conditions, even removal of a blanket for improving detection accuracy would be considered an unpleasant obtrusive measure. After all, vital signal detection becomes even more difficult since amplitudes and/or nominal values of disturbing signal components are expected to be much larger than amplitudes and/or nominal values of desired signal components to be extracted. Potentially the magnitude of difference between the respective components (e.g., global motion vs. respiration motion) can be expected to even comprise several orders.
A possible approach to this challenge may be directed to providing well-prepared and steady ambient conditions when capturing a signal of interest in which the desired vital signal component is embedded. A minimization of potentially occurring disturbing signal components can be achieved in this way. However, such “laboratory” conditions cannot be transferred into everyday field applications and environments since high efforts and much preparation work would be required therefore.
The required preparation work might comprise, for instance, installation and orientation of several defined standard light sources and, moreover, measures for fixation of the subject to be observed and of the monitoring device so as to avoid disturbing motion. It is considered unlikely that these measures are applicable in everyday environments, such as ambulant or clinical patient monitoring, sleep monitoring, or even in lifestyle environments like sporting and fitness monitoring.